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on Knowledge Management and Knowledge Economy |
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Issue of 2020‒10‒12
five papers chosen by Laura Ştefănescu Centrul European de Studii Manageriale în Administrarea Afacerilor |
| By: | Maria Tsouri; ; |
| Abstract: | The proximity literature usually treats proximity in terms of common attributes shared by agents, disregarding the relative position of an actor inside the network. This paper discusses the importance of such dimension of proximity, labelled as in-network proximity, and proposes an empirical measurement for it, assessing its impact (jointly with other dimensions of proximity) on the creation of strong knowledge network ties in ICT in the region of Trentino. The findings show that actors with higher in-network proximity are more attractive for both other central actors and peripheral ones, which is further strengthening their position within the network. |
| Keywords: | knowledge networks, in-network proximity, strong ties, proximity dimensions |
| Date: | 2020–09 |
| URL: | http://d.repec.org/n?u=RePEc:egu:wpaper:2045&r=all |
| By: | Stefano Basilico (Friedrich Schiller University Jena, Faculty of Economics and Business Administration); Holger Graf (Friedrich Schiller University Jena, Faculty of Economics and Business Administration) |
| Abstract: | The concept of Bridging Technologies (BTs) refers to technologies which are important for the regional knowledge base by connecting different fields and thereby enabling technological development. We provide analytical tools to identify BTs and study their evolution over time. We apply these tools on several levels. Our findings indicate that large patenting regions are not necessarily the ones that embed most new technologies in their Knowledge Space (KS). Our findings reveal that the German KS became less dependent on important technologies, such as transport, machinery and chemicals over the period 1995-2015. Changes in the German KS in terms of the development of new BTs are due to a regionally dispersed process rather than driven by single regions. |
| Keywords: | Knowledge Spaces, Network Analysis, Bridging Technology, Revealed Relatedness, GPT, Centrality |
| JEL: | O33 O34 R11 |
| Date: | 2020–09–10 |
| URL: | http://d.repec.org/n?u=RePEc:jrp:jrpwrp:2020-012&r=all |
| By: | Christopher R. Esposito; ; |
| Abstract: | This article studies how new locations emerge as advantageous places for the creation of ideas. Analysis of a novel patent-based dataset that traces the flow of knowledge between inventions and across time reveals that inventors initiate knowledge production in new places through a three-stage process. In the first stage, about 50 years before knowledge production in a region reaches an appreciable volume, local inventors begin to experiment with a few promising ideas developed in other places. In the second stage, inventors use the promising ideas developed elsewhere to create a large number of highly impactful inventions locally. In the third stage, inventors source high-impact ideas from their local environs and produce an even larger number of inventions, albeit of lower quality. Overall knowledge production in regions peaks in this third stage, but novelty and the potential for future knowledge growth decline. |
| Keywords: | Regional development, innovation, knowledge transmission, agglomeration |
| JEL: | O33 R12 |
| Date: | 2020–09 |
| URL: | http://d.repec.org/n?u=RePEc:egu:wpaper:2046&r=all |
| By: | Sergey Kichko; Wen-Jung Liang; Chao-Cheng Mai; Jacques-Francois Thisse; Ping Wang |
| Abstract: | Tech clusters play a growing role in knowledge-based economies by accommodating high-tech firms and providing an environment that fosters location-dependent knowledge spillovers and promote R&D investments by .rms. Yet, not much is known about the economic conditions under which such entities may form in equilibrium without government interventions. This paper develops a spatial equilibrium model with a competitive final sector and a monopolistically competitive intermediate sector, which allows us to determine necessary and sufficient conditions for a tech cluster to emerge as an equilibrium outcome. We show that strongly localized knowledge spillovers, skilled labor abundance, and low commuting costs are key drivers for a tech cluster to form. Not only is the productivity of the final sector higher when intermediate firms cluster, but a tech cluster hosts more intermediate firms and more R&D and production activities, and yields greater worker welfare, compared to what a dispersed pattern would generate. With continual improvements in infrastructure and communication technology that lowers coordination costs, tech clusters will eventually be fragmented. |
| Keywords: | high-tech city, knowledge spillovers, intermediate firm clustering, land use, commuting, R&D |
| JEL: | D51 L22 O33 R13 |
| Date: | 2020 |
| URL: | http://d.repec.org/n?u=RePEc:ces:ceswps:_8527&r=all |
| By: | Giulio Cornelli; Jon Frost; Leonardo Gambacorta; Raghavendra Rau; Robert Wardrop; Tania Ziegler |
| Abstract: | Fintech and big tech platforms have expanded their lending around the world. We estimate that the flow of these new forms of credit reached USD 223 billion and USD 572 billion in 2019, respectively. China, the United States and the United Kingdom are the largest markets for fintech credit. Big tech credit is growing fast in China, Japan, Korea, Southeast Asia and some countries in Africa and Latin America. Cross-country panel regressions show that such lending is more developed in countries with higher GDP per capita (at a declining rate), where banking sector mark-ups are higher and where banking regulation is less stringent. Fintech credit is larger where there are fewer bank branches per capita. We also find that fintech and big tech credit are more developed where the ease of doing business is greater, and investor protection disclosure and the efficiency of the judicial system are more advanced, the bank creditto- deposit ratio is lower and where bond and equity markets are more developed. Overall, alternative credit seems to complement other forms of credit, rather than substitute for them. |
| Keywords: | fintech, big tech, credit, data, technology, digital innovation |
| Date: | 2020–09 |
| URL: | http://d.repec.org/n?u=RePEc:bis:biswps:887&r=all |